| A nonlinear dynamical plant of arbitrary relative degree and possibly nonminimum phase is considered. The control objective is asymptotic tracking of a desired output trajectory without knowledge of the desired state trajectory; as is often the case in practice. An approximate plant model of lower order is assumed known but only the physical plant's output is considered available for measurement.; This research consists of the formulation and analysis of an output controller for the above objective. Block input-output (BIO) techniques are applied to obtain a square MIMO discrete plant model. This model is controlled via an inner feedback loop for discrete-time tracking of a desired state trajectory which, in turn, is estimated via an outer learning control loop. Robustness of the controller to parameter mismatch, disturbances, and unmodeled dynamics are demonstrated in simulations of a flexible arm in a vertical plane.; The controller is implemented numerically but formulated as static functional mappings for: (a) implementation feasibility since closed-form solutions will not exist in general, (b) extension to the output control of systems with more outputs than inputs (appears to have no continuous-time solution), and (c) possible application of Neural Networks for on-line identification and parallel computation of the controller.; Application areas include output control of under-actuated, nonminimum phase, and/or non feedback-linearizable systems including flexible and free-flying manipulators, satellite structures, disk-drives, and land vehicle steering and navigation. |
